Transforming Healthcare Through Artificial Intelligence: From Predictive Diagnostics to Personalized Therapeutics

Abstract

Artificial intelligence (AI) is revolutionizing medicine by enabling earlier detection of disease and tailoring treatments to individual patients. In healthcare, machine learning and deep learning can analyze complex data from images, genetic tests, and electronic records to predict illness before symptoms appear and to design personalized therapies. For example, AI algorithms now detect cancers in medical images as accurately as specialists and identify which patients will best respond to a drug. This paper reviews recent advances in AI-powered diagnostics and treatment. We discuss AI in radiology and pathology, AI models using electronic health data, and AI-driven genomics and drug discovery. Ethical and practical challenges such as data bias, privacy, and clinical validation are also addressed. Finally, we present representative experiments using public datasets (e.g. cancer diagnostics) and survey real-world deployments. The evidence shows AI systems can significantly improve accuracy and efficiency in medical decision-making, paving the way for more predictive and personalized healthcare.